Written by the leading expert in the field, this text reviews the
major new developments in envelope models and methods
An Introduction to Envelopes provides an overview of the theory and
methods of envelopes, a class of procedures for increasing efficiency in
multivariate analyses without altering traditional objectives. The
author offers a balance between foundations and methodology by
integrating illustrative examples that show how envelopes can be used in
practice. He discusses how to use envelopes to target selected
coefficients and explores predictor envelopes and their connection with
partial least squares regression. The book reveals the potential for
envelope methodology to improve estimation of a multivariate mean.
The text also includes information on how envelopes can be used in
generalized linear models, regressions with a matrix-valued response,
and reviews work on sparse and Bayesian response envelopes. In addition,
the text explores relationships between envelopes and other dimension
reduction methods, including canonical correlations, reduced-rank
regression, supervised singular value decomposition, sufficient
dimension reduction, principal components, and principal fitted
components. This important resource:
- Offers a text written by the leading expert in this field
- Describes groundbreaking work that puts the focus on this burgeoning
area of study
- Covers the important new developments in the field and highlights the
most important directions
- Discusses the underlying mathematics and linear algebra
- Includes an online companion site with both R and Matlab support
Written for researchers and graduate students in multivariate analysis
and dimension reduction, as well as practitioners interested in
statistical methodology, An Introduction to Envelopes offers the first
book on the theory and methods of envelopes.
